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fix npu-model prompt (#12057)

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Zijie Li 2024-09-11 10:06:45 +08:00 committed by GitHub
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2 changed files with 2 additions and 3 deletions
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python/llm/example/NPU/HF-Transformers-AutoModels/LLM/README.md
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@ -62,7 +62,7 @@ python ./generate.py
Arguments info: Arguments info:
- `--repo-id-or-model-path REPO_ID_OR_MODEL_PATH`: argument defining the huggingface repo id for the Llama2 model (e.g. `meta-llama/Llama-2-7b-chat-hf`) to be downloaded, or the path to the huggingface checkpoint folder. It is default to be `'meta-llama/Llama-2-7b-chat-hf'`, and more verified models please see the list in [Verified Models](#verified-models). - `--repo-id-or-model-path REPO_ID_OR_MODEL_PATH`: argument defining the huggingface repo id for the Llama2 model (e.g. `meta-llama/Llama-2-7b-chat-hf`) to be downloaded, or the path to the huggingface checkpoint folder. It is default to be `'meta-llama/Llama-2-7b-chat-hf'`, and more verified models please see the list in [Verified Models](#verified-models).
- `--lowbit-path LOWBIT_MODEL_PATH`: argument defining the path to save/load lowbit version of the model. If it is an empty string, the original pretrained model specified by `REPO_ID_OR_MODEL_PATH` will be loaded. If it is an existing path, the lowbit model in `LOWBIT_MODEL_PATH` will be loaded. If it is a non-existing path, the original pretrained model specified by `REPO_ID_OR_MODEL_PATH` will be loaded, and the converted lowbit version will be saved into `LOWBIT_MODEL_PATH`. It is default to be `''`, i.e. an empty string. - `--lowbit-path LOWBIT_MODEL_PATH`: argument defining the path to save/load lowbit version of the model. If it is an empty string, the original pretrained model specified by `REPO_ID_OR_MODEL_PATH` will be loaded. If it is an existing path, the lowbit model in `LOWBIT_MODEL_PATH` will be loaded. If it is a non-existing path, the original pretrained model specified by `REPO_ID_OR_MODEL_PATH` will be loaded, and the converted lowbit version will be saved into `LOWBIT_MODEL_PATH`. It is default to be `''`, i.e. an empty string.
- `--prompt PROMPT`: argument defining the prompt to be infered (with integrated prompt format for chat). It is default to be `'Once upon a time, there existed a little girl who liked to have adventures. She wanted to go to places and meet new people, and have fun'`. - `--prompt PROMPT`: argument defining the prompt to be infered. It is default to be `'Once upon a time, there existed a little girl who liked to have adventures. She wanted to go to places and meet new people, and have fun'`.
- `--n-predict N_PREDICT`: argument defining the max number of tokens to predict. It is default to be `32`. - `--n-predict N_PREDICT`: argument defining the max number of tokens to predict. It is default to be `32`.
- `--load_in_low_bit`: argument defining the `load_in_low_bit` format used. It is default to be `sym_int8`, `sym_int4` can also be used. - `--load_in_low_bit`: argument defining the `load_in_low_bit` format used. It is default to be `sym_int8`, `sym_int4` can also be used.

3
python/llm/example/NPU/HF-Transformers-AutoModels/LLM/generate.py
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@ -66,8 +66,7 @@ if __name__ == '__main__':
model.save_low_bit(args.lowbit_path) model.save_low_bit(args.lowbit_path)
with torch.inference_mode(): with torch.inference_mode():
prompt = "Once upon a time, there existed a little girl who liked to have adventures. She wanted to go to places and meet new people, and have fun" input_ids = tokenizer.encode(args.prompt, return_tensors="pt")
input_ids = tokenizer.encode(prompt, return_tensors="pt")
print("finish to load") print("finish to load")
print('input length:', len(input_ids[0])) print('input length:', len(input_ids[0]))
st = time.time() st = time.time()